Answer To: Page 1 of 6 INFS 4020 – Big Data Concepts Assignment 1: Technology Review (SP2 2022) DUE: By 11PM...
Chirag answered on Apr 23 2022
INFS 4020 – Big Data Concepts (SP2 2022)
Assignment 1 – Technology Review
[Your Name]
[Date]
Contents
Introduction 3
Overview of [your chosen industry] 3
Overview of [your chosen AI technology/technique] 3
Limitations and Issues to Using [your chosen technology] 3
References 3
Introduction
Artificial intelligence (AI) is a fascinating technology in our digital age, and its practical applications throughout the economy are rapidly expanding. Machine learning approaches include neural networks as a subset. They're AI systems that simulate connected "neural units," loosely modelled after the way neurons interact in the brain. Deep learning has a significant impact on various industries that contribute to our economy: agriculture, biotechnology, retail, oil and gas, supply chain, genetics, etc. With the help of machines and suitable deep learning techniques, a huge impact can be made on how our business works and operates. More efficient control can be established over things, and more efficient business decisions can be taken if we have good and accurate predictions with us, and more and good accuracy can be achieved using deep learning techniques.
Overview of [your chosen industry]
Agriculture is a vital part of the global economy and provides for one of humanity's most fundamental needs, namely food. It is regarded as the primary employment source in the majority of countries. It is one of the high revenue-generating sectors, and the contribution to GDP of this industry is very high. It is necessary to focus on improving the agriculture industry's resource management, which will eventually help in more revenue and more food resources. This can be achieved by careful planning and approaches in Artificial intelligence for wise decision making and improved business functionality across the world.
Farmers often follow the processes outlined below when completing agricultural operations.
Step 1: Picking a Crop
Step 2: Prepare the Land
Step 3: Planting the Seeds
Step 4: Fertilization and irrigation
Step 5: Crop Maintenance (pesticides, crop pruning, and so forth).
Step 6: Harvesting
Step 7: Post-Harvesting activities
Overview of [your chosen AI technology/technique]
Daily, deep learning technology advances. According to the conclusions of this study, the use of CNN in agriculture is every day, and it produces excellent outcomes in every single stage of the agriculture industry. We can see how useful it can be. The CNN's learning capacity and accuracy are boosted using depth, other structures, and hardware support. There are still issues like dataset development, training and testing time, hardware support, deploying huge models on small devices like boards or Android phones, and user awareness, to name a few.
A convolutional neural network is a class of deep neural networks, most commonly applied to analyze visual imagery. It consists of a convolutional layer, pooling layer, flattening layer, and dense neural network.
Convent models are easy and faster to train on images compared to other models. It helps in position invariant feature detection with the help of convolutional filters. Feature selection is not required because we have convolutional neural network filters. We have image data in RGB scale that leads to very high computation, which the help of the pooling layer will resolve. And then, the final vector after flattening is going in the model.
Using [your chosen...